| The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks M Berman, A Rannen Triki, MB Blaschko | 1185 | 2018 |
| Encoder based lifelong learning A Rannen-Triki*, R Aljundi*, MB Blaschko, ... Proceedings of the IEEE International Conference on Computer Vision, 1320-1328, 2017 | 432 | 2017 |
| A Bayesian optimization framework for neural network compression X Ma*, A Rannen-Triki*, M Berman, C Sagonas, J Cali, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 29 | 2019 |
| NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research J Bornschein*, A Galashov*, R Hemsley*, A Rannen-Triki*, Y Chen, ... JMLR 24, 1-77, 2023 | 22 | 2023 |
| Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks AR Triki, MB Blaschko, YM Jung, S Song, HJ Han, SI Kim, C Joo Computerized medical imaging and graphics 69, 21-32, 2018 | 21 | 2018 |
| Revisiting evaluation metrics for semantic segmentation: Optimization and evaluation of fine-grained intersection over union Z Wang, M Berman, A Rannen-Triki, P Torr, D Tuia, T Tuytelaars, LV Gool, ... Advances in Neural Information Processing Systems 36, 60144-60225, 2023 | 19 | 2023 |
| On the role of optimization in double descent: A least squares study I Kuzborskij, C Szepesvári, O Rivasplata, A Rannen-Triki, R Pascanu Advances in Neural Information Processing Systems 34, 29567-29577, 2021 | 15 | 2021 |
| Function norms for neural networks A Rannen-Triki, M Berman, V Kolmogorov, MB Blaschko Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 15* | 2019 |
| Kalman filter for online classification of non-stationary data MK Titsias, A Galashov, A Rannen-Triki, R Pascanu, YW Teh, ... arXiv preprint arXiv:2306.08448, 2023 | 6 | 2023 |
| Towards better visual explanations for deep image classifiers A Grabska-Barwinska, A Rannen-Triki, O Rivasplata, A György eXplainable AI approaches for debugging and diagnosis., 2021 | 4 | 2021 |
| Towards robust and efficient continual language learning A Fisch, A Rannen-Triki, R Pascanu, J Bornschein, A Lazaridou, ... arXiv preprint arXiv:2307.05741, 2023 | 3 | 2023 |
| Towards compute-optimal transfer learning M Caccia, A Galashov, A Douillard, A Rannen-Triki, D Rao, M Paganini, ... arXiv preprint arXiv:2304.13164, 2023 | 3 | 2023 |
| Mind the Graph When Balancing Data for Fairness or Robustness J Schrouff, A Bellot, A Rannen-Triki, A Malek, I Albuquerque, A Gretton, ... arXiv preprint arXiv:2406.17433, 2024 | 2 | 2024 |
| Transformers for supervised online continual learning J Bornschein, Y Li, A Rannen-Triki arXiv preprint arXiv:2403.01554, 2024 | 1 | 2024 |
| Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models A Rannen-Triki, J Bornschein, R Pascanu, M Hutter, A György, ... arXiv preprint arXiv:2403.01518, 2024 | 1 | 2024 |
| Function Norms for Neural Networks: Theory and Applications A Rannen Ep Triki | | 2020 |
| Yes, IoU loss is submodular-as a function of the mispredictions M Berman, MB Blaschko, AR Triki, J Yu arXiv preprint arXiv:1809.01845, 2018 | | 2018 |
Matthew BlaschkoKU LeuvenVerified email at esat.kuleuven.be
